Liu, Ji

102 publications

AAAI 2025 EGSRAL: An Enhanced 3D Gaussian Splatting Based Renderer with Automated Labeling for Large-Scale Driving Scene Yixiong Huo, Guangfeng Jiang, Hongyang Wei, Ji Liu, Song Zhang, Han Liu, Xingliang Huang, Mingjie Lu, Jinzhang Peng, Dong Li, Lu Tian, Emad Barsoum

NeurIPS 2025 Týr-the-Pruner: Structural Pruning LLMs via Global Sparsity Distribution Optimization Guanchen Li, Yixing Xu, Zeping Li, Ji Liu, Xuanwu Yin, Dong Li, Emad Barsoum

TMLR 2024 Byzantine-Resilient Decentralized Multi-Armed Bandits Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu

NeurIPS 2024 DiP-GO: A Diffusion Pruner via Few-Step Gradient Optimization Haowei Zhu, Dehua Tang, Ji Liu, Mingjie Lu, Jintu Zheng, Jinzhang Peng, Dong Li, Yu Wang, Fan Jiang, Lu Tian, Spandan Tiwari, Ashish Sirasao, Junhai Yong, Bin Wang, Emad Barsoum

AAAI 2024 FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update Ji Liu, Juncheng Jia, Tianshi Che, Chao Huo, Jiaxiang Ren, Yang Zhou, Huaiyu Dai, Dejing Dou

AAAI 2024 G-LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint) Xuhong Li, Haoyi Xiong, Xingjian Li, Xiao Zhang, Ji Liu, Haiyan Jiang, Zeyu Chen, Dejing Dou

AISTATS 2024 Sampling-Based Safe Reinforcement Learning for Nonlinear Dynamical Systems Wesley Suttle, Vipul Kumar Sharma, Krishna Chaitanya Kosaraju, Sivaranjani Seetharaman, Ji Liu, Vijay Gupta, Brian M Sadler

AAAI 2024 UPDP: A Unified Progressive Depth Pruner for CNN and Vision Transformer Ji Liu, Dehua Tang, Yuanxian Huang, Li Zhang, Xiaocheng Zeng, Dong Li, Mingjie Lu, Jinzhang Peng, Yu Wang, Fan Jiang, Lu Tian, Ashish Sirasao

IJCAI 2023 Accurate MRI Reconstruction via Multi-Domain Recurrent Networks Jinbao Wei, Zhijie Wang, Kongqiao Wang, Li Guo, Xueyang Fu, Ji Liu, Xun Chen

CVPRW 2023 AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection Wentao Zhu, Yufang Huang, Xiufeng Xie, Wenxian Liu, Jincan Deng, Debing Zhang, Zhangyang Wang, Ji Liu

ICML 2023 Fast Federated Machine Unlearning with Nonlinear Functional Theory Tianshi Che, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Ji Liu, Da Yan, Dejing Dou, Jun Huan

CVPR 2023 LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising Zichun Wang, Ying Fu, Ji Liu, Yulun Zhang

AAAI 2023 PINAT: A Permutation INvariance Augmented Transformer for NAS Predictor Shun Lu, Yu Hu, Peihao Wang, Yan Han, Jianchao Tan, Jixiang Li, Sen Yang, Ji Liu

ICCV 2023 Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction Miaoyu Li, Ying Fu, Ji Liu, Yulun Zhang

AAAI 2023 ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-Cost Proxies Yu Shen, Yang Li, Jian Zheng, Wentao Zhang, Peng Yao, Jixiang Li, Sen Yang, Ji Liu, Bin Cui

AAAI 2023 Quality-Aware Self-Training on Differentiable Synthesis of Rare Relational Data Chongsheng Zhang, Yaxin Hou, Ke Chen, Shuang Cao, Gaojuan Fan, Ji Liu

CVPR 2023 Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising Miaoyu Li, Ji Liu, Ying Fu, Yulun Zhang, Dejing Dou

ICML 2022 Accelerated Federated Learning with Decoupled Adaptive Optimization Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou

ECCV 2022 Bandwidth-Aware Adaptive Codec for DNN Inference Offloading in IoT Xiufeng Xie, Ning Zhou, Wentao Zhu, Ji Liu

CVPR 2022 Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification Haowei Zhu, Wenjing Ke, Dong Li, Ji Liu, Lu Tian, Yi Shan

CVPR 2022 Dynamic Sparse R-CNN Qinghang Hong, Fengming Liu, Dong Li, Ji Liu, Lu Tian, Yi Shan

AAAI 2022 Efficient Device Scheduling with Multi-Job Federated Learning Chendi Zhou, Ji Liu, Juncheng Jia, Jingbo Zhou, Yang Zhou, Huaiyu Dai, Dejing Dou

IJCAI 2022 FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server Hong Zhang, Ji Liu, Juncheng Jia, Yang Zhou, Huaiyu Dai, Dejing Dou

NeurIPS 2022 Improving Certified Robustness via Statistical Learning with Logical Reasoning Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlaš, Ji Liu, Heng Guo, Ce Zhang, Bo Li

ECCV 2022 Multi-Granularity Pruning for Model Acceleration on Mobile Devices Tianli Zhao, Xi Sheryl Zhang, Wentao Zhu, Jiaxing Wang, Sen Yang, Ji Liu, Jian Cheng

ICLR 2022 Unified Visual Transformer Compression Shixing Yu, Tianlong Chen, Jiayi Shen, Huan Yuan, Jianchao Tan, Sen Yang, Ji Liu, Zhangyang Wang

ICML 2021 1-Bit Adam: Communication Efficient Large-Scale Training with Adam’s Convergence Speed Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He

MLJ 2021 AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow Haiyan Jiang, Haoyi Xiong, Dongrui Wu, Ji Liu, Dejing Dou

AAAI 2021 C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak Congxi Xiao, Jingbo Zhou, Jizhou Huang, An Zhuo, Ji Liu, Haoyi Xiong, Dejing Dou

ICML 2021 DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu

CVPRW 2021 E2VTS: Energy-Efficient Video Text Spotting from Unmanned Aerial Vehicles Zhenyu Hu, Pengcheng Pi, Zhenyu Wu, Yunhe Xue, Jiayi Shen, Jianchao Tan, Xiangru Lian, Zhangyang Wang, Ji Liu

NeurIPS 2021 ErrorCompensatedX: Error Compensation for Variance Reduced Algorithms Hanlin Tang, Yao Li, Ji Liu, Ming Yan

ICCV 2021 GDP: Stabilized Neural Network Pruning via Gates with Differentiable Polarization Yi Guo, Huan Yuan, Jianchao Tan, Zhangyang Wang, Sen Yang, Ji Liu

ICCV 2021 Hand Image Understanding via Deep Multi-Task Learning Xiong Zhang, Hongsheng Huang, Jianchao Tan, Hongmin Xu, Cheng Yang, Guozhu Peng, Lei Wang, Ji Liu

ICCV 2021 Improving Low-Precision Network Quantization via Bin Regularization Tiantian Han, Dong Li, Ji Liu, Lu Tian, Yi Shan

AAAI 2021 Optimizing Information Theory Based Bitwise Bottlenecks for Efficient Mixed-Precision Activation Quantization Xichuan Zhou, Kui Liu, Cong Shi, Haijun Liu, Ji Liu

ICLR 2021 Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments Daochen Zha, Wenye Ma, Lei Yuan, Xia Hu, Ji Liu

CVPR 2021 RankDetNet: Delving into Ranking Constraints for Object Detection Ji Liu, Dong Li, Rongzhang Zheng, Lu Tian, Yi Shan

ICML 2021 Reinforcement Learning for Cost-Aware Markov Decision Processes Wesley Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David Kraemer

ICCV 2021 ResRep: Lossless CNN Pruning via Decoupling Remembering and Forgetting Xiaohan Ding, Tianxiang Hao, Jianchao Tan, Ji Liu, Jungong Han, Yuchen Guo, Guiguang Ding

NeurIPS 2021 Shifted Chunk Transformer for Spatio-Temporal Representational Learning Xuefan Zha, Wentao Zhu, Lv Xun, Sen Yang, Ji Liu

ICML 2021 Streaming Bayesian Deep Tensor Factorization Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe

NeurIPS 2021 TNASP: A Transformer-Based NAS Predictor with a Self-Evolution Framework Shun Lu, Jixiang Li, Jianchao Tan, Sen Yang, Ji Liu

ICLR 2021 UMEC: Unified Model and Embedding Compression for Efficient Recommendation Systems Jiayi Shen, Haotao Wang, Shupeng Gui, Jianchao Tan, Zhangyang Wang, Ji Liu

NeurIPS 2021 Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, Dejing Dou

AAAI 2020 Deep Embedded Complementary and Interactive Information for Multi-View Classification Jinglin Xu, Wenbin Li, Xinwang Liu, Dingwen Zhang, Ji Liu, Junwei Han

AAAI 2020 Feature Variance Regularization: A Simple Way to Improve the Generalizability of Neural Networks Ranran Huang, Hanbo Sun, Ji Liu, Lu Tian, Li Wang, Yi Shan, Yu Wang

ECCV 2020 GAN Slimming: All-in-One GAN Compression by a Unified Optimization Framework Haotao Wang, Shupeng Gui, Haichuan Yang, Ji Liu, Zhangyang Wang

ECCV 2020 Hand-Transformer: Non-Autoregressive Structured Modeling for 3D Hand Pose Estimation Lin Huang, Jianchao Tan, Ji Liu, Junsong Yuan

NeurIPS 2020 Once-for-All Adversarial Training: In-Situ Tradeoff Between Robustness and Accuracy for Free Haotao Wang, Tianlong Chen, Shupeng Gui, TingKuei Hu, Ji Liu, Zhangyang Wang

ICLR 2020 Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search Anji Liu, Jianshu Chen, Mingze Yu, Yu Zhai, Xuewen Zhou, Ji Liu

AISTATS 2019 AutoML from Service Provider’s Perspective: Multi-Device, Multi-Tenant Model Selection with GP-EI Chen Yu, Bojan Karlaš, Jie Zhong, Ce Zhang, Ji Liu

ICML 2019 Distributed Learning over Unreliable Networks Chen Yu, Hanlin Tang, Cedric Renggli, Simon Kassing, Ankit Singla, Dan Alistarh, Ce Zhang, Ji Liu

ICML 2019 DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression Hanlin Tang, Chen Yu, Xiangru Lian, Tong Zhang, Ji Liu

NeurIPS 2019 Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent Wenqing Hu, Chris Junchi Li, Xiangru Lian, Ji Liu, Huizhuo Yuan

ICLR 2019 Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking Haichuan Yang, Yuhao Zhu, Ji Liu

NeurIPS 2019 Global Sparse Momentum SGD for Pruning Very Deep Neural Networks Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Jungong Han, Ji Liu

NeurIPS 2019 LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning Yali Du, Lei Han, Meng Fang, Ji Liu, Tianhong Dai, Dacheng Tao

ICLR 2019 Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications Carson Eisenach, Haichuan Yang, Ji Liu, Han Liu

NeurIPS 2019 Model Compression with Adversarial Robustness: A Unified Optimization Framework Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu

AAAI 2019 Optimal Projection Guided Transfer Hashing for Image Retrieval Ji Liu, Lei Zhang

AISTATS 2019 Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization Xiangru Lian, Ji Liu

ICML 2018 $d^2$: Decentralized Training over Decentralized Data Hanlin Tang, Xiangru Lian, Ming Yan, Ce Zhang, Ji Liu

AAAI 2018 Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization Zhouyuan Huo, Bin Gu, Ji Liu, Heng Huang

ICML 2018 Asynchronous Decentralized Parallel Stochastic Gradient Descent Xiangru Lian, Wei Zhang, Ce Zhang, Ji Liu

NeurIPS 2018 Communication Compression for Decentralized Training Hanlin Tang, Shaoduo Gan, Ce Zhang, Tong Zhang, Ji Liu

NeurIPS 2018 Gradient Sparsification for Communication-Efficient Distributed Optimization Jianqiao Wangni, Jialei Wang, Ji Liu, Tong Zhang

IJCAI 2018 New Balanced Active Learning Model and Optimization Algorithm Xiaoqian Wang, Yijun Huang, Ji Liu, Heng Huang

JAIR 2018 Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity Bo Liu, Ian Gemp, Mohammad Ghavamzadeh, Ji Liu, Sridhar Mahadevan, Marek Petrik

NeurIPS 2018 Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity Conghui Tan, Tong Zhang, Shiqian Ma, Ji Liu

JMLR 2017 Accelerating Stochastic Composition Optimization Mengdi Wang, Ji Liu, Ethan X. Fang

NeurIPS 2017 Can Decentralized Algorithms Outperform Centralized Algorithms? a Case Study for Decentralized Parallel Stochastic Gradient Descent Xiangru Lian, Ce Zhang, Huan Zhang, Cho-Jui Hsieh, Wei Zhang, Ji Liu

AISTATS 2017 Finite-Sum Composition Optimization via Variance Reduced Gradient Descent Xiangru Lian, Mengdi Wang, Ji Liu

IJCAI 2017 No Learner Left Behind: On the Complexity of Teaching Multiple Learners Simultaneously Xiaojin Zhu, Ji Liu, Manuel Lopes

ICML 2017 On the Projection Operator to a Three-View Cardinality Constrained Set Haichuan Yang, Shupeng Gui, Chuyang Ke, Daniel Stefankovic, Ryohei Fujimaki, Ji Liu

ICML 2017 ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang

NeurIPS 2016 A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order Xiangru Lian, Huan Zhang, Cho-Jui Hsieh, Yijun Huang, Ji Liu

NeurIPS 2016 Accelerating Stochastic Composition Optimization Mengdi Wang, Ji Liu, Ethan Fang

NeurIPS 2016 Asynchronous Parallel Greedy Coordinate Descent Yang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S Dhillon, James Demmel, Cho-Jui Hsieh

UAI 2016 Dantzig Selector with an Approximately Optimal Denoising Matrix and Its Application in Sparse Reinforcement Learning Bo Liu, Luwan Zhang, Ji Liu

CVPR 2016 On Benefits of Selection Diversity via Bilevel Exclusive Sparsity Haichuan Yang, Yijun Huang, Lam Tran, Ji Liu, Shuai Huang

AAAI 2016 Optimal Discrete Matrix Completion Zhouyuan Huo, Ji Liu, Heng Huang

AAAI 2016 Privacy-CNH: A Framework to Detect Photo Privacy with Convolutional Neural Network Using Hierarchical Features Lam Tran, Deguang Kong, Hongxia Jin, Ji Liu

IJCAI 2016 Proximal Gradient Temporal Difference Learning Algorithms Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

IJCAI 2016 Staleness-Aware Async-SGD for Distributed Deep Learning Wei Zhang, Suyog Gupta, Xiangru Lian, Ji Liu

ICML 2016 The Teaching Dimension of Linear Learners Ji Liu, Xiaojin Zhu, Hrag Ohannessian

JMLR 2016 The Teaching Dimension of Linear Learners Ji Liu, Xiaojin Zhu

AAAI 2016 Uncorrelated Group LASSO Deguang Kong, Ji Liu, Bo Liu, Xuan Bao

JMLR 2015 An Asynchronous Parallel Stochastic Coordinate Descent Algorithm Ji Liu, Stephen J. Wright, Christopher Ré, Victor Bittorf, Srikrishna Sridhar

NeurIPS 2015 Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu

UAI 2015 Finite-Sample Analysis of Proximal Gradient TD Algorithms Bo Liu, Ji Liu, Mohammad Ghavamzadeh, Sridhar Mahadevan, Marek Petrik

ICML 2014 An Asynchronous Parallel Stochastic Coordinate Descent Algorithm Ji Liu, Steve Wright, Christopher Re, Victor Bittorf, Srikrishna Sridhar

NeurIPS 2014 Exclusive Feature Learning on Arbitrary Structures via $\ell_{1,2}$-Norm Deguang Kong, Ryohei Fujimaki, Ji Liu, Feiping Nie, Chris Ding

ICML 2014 Forward-Backward Greedy Algorithms for General Convex Smooth Functions over a Cardinality Constraint Ji Liu, Jieping Ye, Ryohei Fujimaki

ECCV 2014 Spectral Clustering with a Convex Regularizer on Millions of Images Maxwell D. Collins, Ji Liu, Jia Xu, Lopamudra Mukherjee, Vikas Singh

NeurIPS 2013 An Approximate, Efficient LP Solver for LP Rounding Srikrishna Sridhar, Stephen Wright, Christopher Re, Ji Liu, Victor Bittorf, Ce Zhang

ICML 2013 Guaranteed Sparse Recovery Under Linear Transformation Ji Liu, Lei Yuan, Jieping Ye

JMLR 2012 A Multi-Stage Framework for Dantzig Selector and LASSO Ji Liu, Peter Wonka, Jieping Ye

NeurIPS 2012 Regularized Off-Policy TD-Learning Bo Liu, Sridhar Mahadevan, Ji Liu

CVPR 2011 Sparse Reconstruction Cost for Abnormal Event Detection Yang Cong, Junsong Yuan, Ji Liu

NeurIPS 2010 Multi-Stage Dantzig Selector Ji Liu, Peter Wonka, Jieping Ye

ICCV 2009 Tensor Completion for Estimating Missing Values in Visual Data Ji Liu, Przemyslaw Musialski, Peter Wonka, Jieping Ye